Browsing by Author "Soltanisehat, Leili"

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A comparative assessment of air quality across European countries using an integrated decision support model
(2022-06) Torkayesh, Ali Ebadi; Alizadeh, Reza; Soltanisehat, Leili; Torkayesh, Sajjad Ebadi; Lund, Peter D.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Reducing air pollution including greenhouse gas emissions originating from extensive use of fossil fuels is critical for European countries aiming at improving their environment and at carbon neutrality by the middle of this century. To optimally reduce the air pollutants and mitigate the climate change, not only national or European Union level regulation need to be considered, but also international agreements such as the Sustainable Development Goals, Kyoto Protocol, and Paris Climate Agreement need to be included in these strategies. Managing such a complex framework would benefit from reliable multi-criteria decision-making approaches. Current models to enhance air quality often concentrate on one criterion at a time and focus on momentary improvements only, unable to offer longstanding enhancement. Therefore, comparative analysis of emissions of several air pollutants simultaneously is highly relevant empowering decision-makers with better tools for policy development. The focus of this study is on a decision support model based on the Best-Worst Method and the Measurement of Alternatives and Ranking According to Compromise Solution method to comparatively analyze air pollutants of 22 European countries. This study is the first in its kind to develop an integrated decision model for air quality assessment considering six air pollutants. Extensive sensitivity analyses were performed to highlight the impacts from different scenarios on the decision-making. The results indicate that Sweden, Latvia, France, Lithuania, Hungary, and Italy ranked as the top six countries with the lowest emission. However, Finland, Poland, the Czech Republic, Luxembourg, and Estonia had the lowest overall ranking and the highest per capita emissions. The proposed methodology and evaluation framework can provide a helpful tool for developing regional and national strategies to minimize air pollutants and to improve environmental sustainability.
Improving renewable energy policy planning and decision-making through a hybrid MCDM method
(2020-02) Alizadeh, Reza; Soltanisehat, Leili; Lund, Peter D.; Zamanisabzi, Hamed
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Shifting from fossil to clean energy sources is a major global challenge, but in particular for those countries with substantial fossil-fuel reserves and economies depending on fossil-fuel exports. Here we introduce an improved framework for renewable energy planning and decision-making to help such countries to more effectively harness their abundant renewable energy resources. We use Iran as a case for the analysis. The framework includes identifying and removing barriers that prevent the use of renewables. It is based on combining two models: Benefit, Opportunity, Cost, Risk (BOCR) and Analytic Network Process (ANP) models. In the analyses, the mutual weight of strategic criteria is employed such as technology, economy, energy vulnerability, security, global effects, and human wellbeing. Using the integrated model, we find that solar energy would be the preferential renewable energy source for Iran. Also, the role of infrastructures, policies, and administrative structures in renewable energy to facilitate their development was analyzed. The renewable energy policy-making framework presented is applicable to other countries as well.
Outlook on biofuels in future studies: A systematic literature review
(2020-12) Alizadeh, Reza; Lund, Peter D.; Soltanisehat, Leili
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
Foresight methods are useful for long-range planning such as strategic energy management, energy policy, and renewable and sustainable energy planning to manage uncertainties. Futures studies may affect the anticipation and speculation of future and emerging technologies. In this paper, biofuels futures are explored based on a critical evaluation of the literature to draw the state-of-the-art for the future-oriented biofuel research. A six-fold typology mapping from two main futures studies methodologies is used. (i) descriptive scenarios, forecasts, and statistical scenarios as descriptive methods; (ii) roadmaps, visions, and backcasts as prescriptive methods. The expectations embodied in the literature are then explored through deriving research challenges about the future of biofuels: (1) the main motives and driving forces in a biofuel era; (2) the main obstacles or difficulties confronting a biofuel era; (3) the plausibility and importance of each of different scenarios; (4) key technological breakthroughs for the bioeconomy; (5) details about development, maturity and flourish; (6) biofuel era's significant achievement. The literature explains a wide range of plausible futures, from centralized systems related to technological breakthroughs to decentralized systems based on small-scale renewable. Fundamental technological elements are uncovered, and a plausible biofuel economy is drawn along with the necessary pathway to reach it. The review shows a general agreement that a biofuel economy would develop gradually, and a prompt shift to biofuels would require powerful governmental support coupled with significant disruptions such as changes in environmental principles of countries, technology breakthroughs, higher oil prices, and urgency of climate change.
Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach
(2020-09) Alizadeh, Reza; Gharizadeh Beiragh, Ramin; Soltanisehat, Leili; Soltanzadeh, Elham; Lund, Peter D.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
To evaluate the performance of complex electricity generation systems, a new dynamic network-based data envelopment analysis (DNDEA) approach is presented. Past data envelopment analysis (DEA) studies on energy system efficiency have often ignored the dynamics of each process of the system individually. Here a network-based DEA method is built, which considers the interrelationships of the operations to determine the efficacy of the system. For assessing the performance over successive periods, with time-based dependencies between the successive periods, a dynamic DEA (DDEA) model is proposed. In DDEA, a linear combination of the efficiencies in successive periods is used as the complement of the system. The network-based and dynamic features of the created model enable measuring the performance of each sub-system process and the entire system in multi-period planning horizons simultaneously. These features make the DEA model identify changes in system efficiencies so much better than the current approaches. The created model is comprehensively implemented in the Iranian electricity sector using real data. Based on the findings, the efficiencies of power generation and transmission sectors are decreasing while the distribution performance is increasing. The proposed model could be applied to electricity generation systems in other countries as well.